Pseudo support vector domain description to train large-size and continuously growing datasets

Author:

El Boujnouni MohamedORCID

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Hardware and Architecture,Human-Computer Interaction,Information Systems,Software

Reference33 articles.

1. Allahyari Y, Sadoghi-Yazdi H (2012) Quasi support vector data description (QSVDD). Int J Signal Process Image Process Pattern Recogn 5(3):65–74

2. Chaudhuri A, Sadek C, Kakde D et al (2021) The trace kernel bandwidth criterion for support vector data description. Pattern Recogn 111:107662

3. Chen X, Cao C, Mai J (2020) Network anomaly detection based on deep support vector data description. In: Proceedings of the 5th IEEE international conference on big data analytics (ICBDA), Xiamen, China

4. Chu SC, Tsang IW, Kwok JT (2004) Scaling up support vector data description by using coresets. In: Proceedings of the international joint conference on neural networks, Budapest, Hungary, pp 425–430

5. Cortes C, Vapnik V (1995) Support-vector network. Mach Learn 20:273–297

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